Production and characterization of methionine γ- lyase from Pseudomonas putida and its effect on cancer cell lines

Introduction and Aim: Cancers are a complex group of genetic illnesses that develop through multistep, mutagenic processes which can invade or spread throughout the body. Recent advances in cancer treatment involve oncolytic viruses to infect and destroy cancer cells. The Newcastle disease virus (NDV), an oncolytic virus has shown to have anti-cancer effects either directly by lysing cancer cells or indirectly by activating the immune system. The green fluorescent protein (GFP) has been widely used in studying the anti-tumor activity of oncolytic viruses. This study aimed to study the anticancer effect of a recombinant rNDV-GFP clone on NCI-H727 lung carcinoma cell line in vitro.   Materials and Methods: The GFP gene was inserted t

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

As a result of rapid industrialization and population development, toxic chemicals have been introduced into water systems in recent decades. Because of its excellent efficiency and simple design, the three-dimensional (3D) electro-Fenton method has been used for the treatment of wastewater. The goal of the current study is to explore the efficiency of phenol removal by the 3D electro-Fenton process, which is one of the advanced oxidation processes (AOPs). In the present work, the effect of the addition of granular activated carbon (GAC) particles to the electro-Fenton system as the third electrode would be investigated in the presence of graphite as the anode and nickel foam as the cathode, which is the source of electro-generated hydrogen

In this study, a new adsorbent derived from sunflower husk powder and coated in CuO nanoparticles (CSFH) was investigated to evaluate the simultaneous adsorption of Levofloxacin (LEV), Meropenem (MER), and Tetracycline (TEC) from an aqueous solution. Significant improvements in the adsorption capacity of the sunflower husk were identified after the powder particles had been coated in CuO nanoparticles. Kinetic data were correlated using a pseudo-second-order model, and was successful for the three antibiotics. Moreover, high compatibility was identified between the LEV, MER, and TEC, isotherm data, and the Langmuir model, which produced a better fit to suit the isotherm curves. In addition, the spontaneous and exothermic nature of the adsor

Introduction: Cutaneous leishmaniasis is considered a parasitic contagion resulting from the flagellated parasite belonging to the genus of Leishmania. Also, cutaneous leishmaniasis is a zoonotic ailment transmitted through the bloodsucking sand-flies bite (belonging to the Phlebotomus genus). The disease's reservoirs included wild or semi-domesticated animals, in general rodents and dogs. Tissue inhibitor metalloproteinase-1 (TIMP-1) is one of the extracellular matrix proteins that have a role in vessel wall degeneration and aneurysm development. In addition, it belongs to the zinc-dependent endopeptidases family that are involved in the degradation of connective tissues proteins which are included in vascular integrity maintenance. The Ge

 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.